Response of global agricultural productivity anomalies to drought stress in irrigated and rainfed agriculture  

作　　者：Xinxin CHEN Lunche WANG Qian CAO Jia SUN Zigeng NIU Liu YANG Weixia JIANG 

机构地区：[1]Hubei Key Laboratory of Regional Ecology and Environmental Change,School of Geography and Information Engineering,China University of Geosciences,Wuhan 430074,China [2]State Key Laboratory of Biogeology and Environmental Geology,China University of Geosciences,Wuhan 430074,China

出　　处：《Science China Earth Sciences》2024年第11期3579-3593,共15页中国科学（地球科学英文版）

基　　金：financially supported by the National Natural Science Foundation of China (Grant Nos. 41925007, 42001314, 41771360, 41975044 & 41801021);the Fundamental Research Funds for National Universities;China University of Geosciences, Wuhan and China Scholarship Council。

摘　　要：The response of agricultural productivity anomalies to drought stress plays a crucial role in the carbon cycle within terrestrial ecosystems and in ensuring food security. However, detailed analysis of how global agricultural productivity anomalies response to drought stress, particularly within irrigated and rainfed agricultural systems, remains insufficient. In this study, the impact of drought stress on agricultural productivity anomalies during the growing season(zcNDVI^(S)), across both irrigated and rainfed agriculture, were analyzed using a suite of hydro-climatic variables. Specifically, the investigation utilized the multi-scalar Standardized Precipitation Evapotranspiration Index(SPEI), the Multivariate ENSO Index(MEI), and the Madden-Julian Oscillation(MJO). Meanwhile, the relationships between hydroclimatic variables and zcNDVI^(S) were analyzed at one, two, three and four months before the ending of growing season(EOS). Results showed that(1) the percentages of significant(p<0.1) drying trends varied across the globe from 8.30% to 13.42%, 6.50% to 14.63%, 6.52% to 14.23%, and 6.47%to 14.95% at one-, two-, three-, and four-month lead times before EOS, respectively, during 2001–2020, which represented by the multiscalar SPEI. This observation highlights that most regions across the globe tend to be arid, which could significantly impact agricultural productivity;(2) the global mean correlation coefficients(rmax) for SPEI-1, SPEI-3, SPEI-6, SPEI-12(indicating SPEI at 1-, 3-, 6-, and 12-month lags), MEI, and MJO with zcNDVI^(S) ranged between 0.24–0.25, 0.27–0.28, 0.25–0.26, 0.21–0.22, –0.02–0.01 and 0.06–0.11, respectively, across both irrigated and rainfed agriculture system from 2001 to 2020.Agricultural productivity anomalies demonstrated a significant correlation with drought stress. The strongest correlations were noted for SPEI-3 and SPEI-6, suggesting a delayed response of crops to drought conditions. This indicates that agriculture ecosystem experiences prolonged disturbances due

关 键 词：Drought Agricultural productivity anomaly Remote sensing MEI and MJO 

分 类 号：S423[农业科学—植物保护]